MongoDB → Yellowfin
AI-first ETL from MongoDB into Yellowfin. Governed entities, incremental sync, typed landing tables.
How Datrise loads MongoDB into Yellowfin
Datrise syncs MongoDB's collections, documents, change streams, and schema snapshots into Yellowfin as warehouse tables Yellowfin builds views on. Flexible or custom fields land in flattened columns, and timestamps such as created, updated, and status changes are typed as date/time dimensions.
Sync is incremental: Datrise uses incremental refresh of the connected tables, so re-runs update only what changed. Date-partitioned facts. Yellowfin views reference columns by name, so Datrise lands stable, well-typed columns to keep reports valid.
Ideal for dashboards with automated data storytelling.
Endpoints
MongoDB: Document database often used as an operational source for analytics.
Yellowfin: BI suite with dashboards, automated insights, and data storytelling.
How MongoDB entities map to Yellowfin
| MongoDB entity | Yellowfin object | Notes |
|---|---|---|
| collections | mongodb_collections | id PK · custom fields → flattened columns |
| documents | mongodb_documents | id PK · linked to mongodb_collections |
| change streams | mongodb_change_streams | date/time dimensions events |
| schema snapshots | mongodb_schema_snapshots | id PK · linked to mongodb_collections |
FAQ
How does Datrise handle MongoDB's custom fields in Yellowfin?
Flexible values are stored as flattened columns, so new fields don't require a migration; strongly-typed fields — dates, numbers, and references — are promoted to native Yellowfin types.
How does the MongoDB to Yellowfin sync stay up to date?
It runs incrementally — Datrise uses incremental refresh of the connected tables.
Related pipelines
More destinations for MongoDB
Early access
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